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At least 667 records · Page 37

Better Plant Data at the Root of Ecosystem Models

Version 2 of the Fine-Root Ecology Database. Fine roots are complex and dynamic structures that serve many critical roles for land plants. Their well-known importance for acquiring water and nutrients and associations with soil microbes underpin many terrestrial processes, including the movement of carbon, nutrients, and water through terrestrial ecosystems. Despite this importance, uncertainty shrouds the traits and processes associated with these enigmatic organs. Such uncertainty limits confidence in our terrestrial biosphere models that incorporate information based on fine-root data. For example, without knowledge of how roots grow and function, scientists struggle to predict how plants and ecosystems will respond to changes in atmospheric carbon dioxide as belowground resources become more limiting to plant growth. To address this challenge, an international group of researchers developed and released in 2017 the first version of a new resource: the Fine-Root Ecology Database (FRED) [Iversen et al., 2017]. Since that time, FRED has undergone significant improvement and additions, culminating in the release of FRED version 2.0 [Iversen et al., 2018]. FRED is a fully open resource containing species-specific as well as mixed-species root trait data that encompass all vegetated terrestrial biomes.

54 ENVIRONMENTAL SCIENCES↗

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe–Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon–use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)–level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. Furthermore, these results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Partitioning Net Ecosystem Exchange (NEE) of CO 2 Using Solar-Induced Chlorophyll Fluorescence (SIF)

Accurate partitioning of net ecosystem exchange (NEE) of CO 2 to gross primary production (GPP) and ecosystem respiration (R eco ) is crucial for understanding carbon cycle dynamics under changing climate. However, it remains as a long-standing problem in global ecology due to lack of independent constraining information for the two offsetting component fluxes. solar-induced chlorophyll fluorescence (SIF), a mechanistic proxy for photosynthesis, holds great promise to improve NEE partitioning by constraining GPP. We developed a parsimonious SIF-based approach for NEE partitioning and examined its performance using synthetic simulations and field measurements. This approach outperforms conventional approaches in reproducing simulated GPP and R eco , especially under high vapor pressure deficit. For field measurements, it results in lower daytime GPP and R eco than conventional approaches. Furthermore, this study made the first attempt to demonstrate SIF's potential for improving NEE partitioning accuracy and sets the stage for future efforts to examine its robustness and scalability under real-world environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature in a Whole Ecosystem Warming Experiment

Abstract Climate warming is expected to accelerate peatland degradation and release rates of carbon dioxide (CO 2 ) and methane (CH 4 ). Spruce and Peatlands Responses Under Changing Environments is an ecosystem‐scale climate manipulation experiment, designed to examine peatland ecosystem response to climate forcings. We examined whether heating up to +9 °C to 3 m‐deep in a peat bog over a 7‐year period led to higher C turnover and CO 2 and CH 4 emissions, by measuring 14 C of solid peat, dissolved organic carbon (DOC), CH 4 , and dissolved CO 2 (DIC). DOC, a major substrate for heterotrophic respiration, increased significantly with warming. There was no 7‐year trend in the DI 14 C of the ambient plots which remained similar to their DO 14 C. At +6.75 °C and +9 °C, the 14 C of DIC, a product of microbial respiration, initially resembled ambient plots but became more depleted over 7 years of warming. We attributed the shifts in DI 14 C to the increasing importance of solid phase peat as a substrate for microbial respiration and quantified this shift via the radiocarbon mass balance. The mass‐balance model revealed increases in peat‐supported respiration of the catotelm depths in heated plots over time and relative to ambient enclosures, from a baseline of 20%–25% in ambient enclosures, to 35%–40% in the heated plots. We find that warming stimulates microorganisms to respire ancient peat C, deposited under prior climate (cooler) conditions. This apparent destabilization of the large peat C reservoir has implications for peatland‐climate feedbacks especially if the balance of the peatland is tipped from net C sink to C source.

54 ENVIRONMENTAL SCIENCES↗

Soil Carbonyl Sulfide (OCS) Fluxes in Terrestrial Ecosystems: An Empirical Model

Measurements of carbonyl sulfide (OCS) enable independent estimates of regional stomatal conductance provided that non-stomatal OCS fluxes are well constrained. OCS is taken up through plant leaves, following the same pathway as CO 2 ; in contrast to CO 2 , OCS is irreversibly destroyed in plant leaves and plants do not typically exhibit OCS emissions. Ecosystem uptake of OCS can indicate changes in stomatal opening. Here we present an empirical model to assess the potential impact of soil OCS exchange, the non-Stomatal OCS exchange Empirical Model (SOCSEM, version 0). We created biome-specific response curves characterizing soil OCS exchange and restricted the model design to require only knowledge of soil moisture and surface temperature because remote sensing observations are available for these two features. Comparing the model to field-based chamber observations reveal deviations that can be attributed to missing complexity of the ground surface (having excluded litter and plants without regulated stomata), shortwave radiation, or the soil environment. For agricultural regions with known net emissions, we use remotely-sensed surface temperature data and demonstrate that data resolution can affect anticipated fluxes. We further investigate the influence of regions with unknown soil OCS responses, for example, Arctic tundra. We compare our model to a process-based and respiration-based soil OCS exchange model that has been implemented in a land surface model. Further field study of tropical and arctic ecosystems in conjunction with studies of non-stomatal surfaces in addition to soil (e.g., bryophytes) will increase confidence in applying OCS as a regional tracer for stomatal conductance.

54 ENVIRONMENTAL SCIENCES↗

Ecosystem Water‐Saving Timescale Varies Spatially With Typical Drydown Length

Abstract Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale ( τ ) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of τ to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of τ that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to τ are measures of the average number of dry days between rainfall events. Values of τ are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem‐level water use strategy.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

Abstract To predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Choi, Jang‐Geun↗

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗

Rising ecosystem water demand exacerbates the lengthening of tropical dry seasons

Precipitation-based assessments show a lengthening of tropical dry seasons under climate change, without considering simultaneous changes in ecosystem water demand. Here, we compare changes in tropical dry season length and timing when dry season is defined as the period when precipitation is less than: its climatological average, potential evapotranspiration, or actual evapotranspiration. While all definitions show more widespread tropical drying than wetting for 1983-2016, we find the largest fraction (48.7%) of tropical land probably experiencing longer dry seasons when dry season is defined as the period when precipitation cannot meet the need of actual evapotranspiration. Southern Amazonia (due to delayed end) and central Africa (due to earlier onset and delayed end) are hotspots of dry season lengthening, with greater certainty when accounting for water demand changes. Therefore, it is necessary to account for changing water demand when characterizing changes in tropical dry periods and ecosystem water deficits.

54 ENVIRONMENTAL SCIENCES↗

Multiple sources of aerobic methane production in aquatic ecosystems include bacterial photosynthesis

Aquatic ecosystems are globally significant sources of the greenhouse gas methane to the atmosphere. Until recently, methane production was thought to be a strictly anaerobic process confined primarily to anoxic sediments. However, supersaturation of methane in oxygenated waters has been consistently observed in lakes and the ocean (termed the ‘methane paradox’), indicating that methane can be produced under oxic conditions through unclear mechanisms. Here we show aerobic methane production from multiple sources in freshwater incubation experiments under different treatments and based on biogeochemical, metagenomic, and metatranscriptomic data. We find that aerobic methane production appears to be associated with (bacterio)chlorophyll metabolism and photosynthesis, as well as with Proteobacterial degradation of methylphosphonate. Genes encoding pathways for putative photosynthetic- and methylphosphonate-based methane production also co-occur in Proteobacterial metagenome-assembled genomes. Our findings provide insight into known mechanisms of aerobic methane production, and suggest a potential co-occurring mechanism associated with bacterial photosynthesis in aquatic ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental warming accelerates positive soil priming in a temperate grassland ecosystem

Abstract Unravelling biosphere feedback mechanisms is crucial for predicting the impacts of global warming. Soil priming, an effect of fresh plant-derived carbon (C) on native soil organic carbon (SOC) decomposition, is a key feedback mechanism that could release large amounts of soil C into the atmosphere. However, the impacts of climate warming on soil priming remain elusive. Here, we show that experimental warming accelerates soil priming by 12.7% in a temperate grassland. Warming alters bacterial communities, with 38% of unique active phylotypes detected under warming. The functional genes essential for soil C decomposition are also stimulated, which could be linked to priming effects. We incorporate lab-derived information into an ecosystem model showing that model parameter uncertainty can be reduced by 32–37%. Model simulations from 2010 to 2016 indicate an increase in soil C decomposition under warming, with a 9.1% rise in priming-induced CO 2 emissions. If our findings can be generalized to other ecosystems over an extended period of time, soil priming could play an important role in terrestrial C cycle feedbacks and climate change.

54 ENVIRONMENTAL SCIENCES↗

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M↗

Threat by marine heatwaves to adaptive large marine ecosystems in an eddy-resolving model

Marine heatwaves (MHWs), episodic periods of abnormally high sea surface temperature, severely affect marine ecosystems. Large marine ecosystems (LMEs) cover ~22% of the global ocean but account for 95% of global fisheries catches. Yet how climate change affects MHWs over LMEs remains unknown because such LMEs are confined to the coast where low-resolution climate models are known to have biases. Here, using a high-resolution Earth system model and applying a ‘future threshold’ that considers MHWs as anomalous warming above the long-term mean warming of sea surface temperatures, we find that future intensity and annual days of MHWs over the majority of the LMEs remain higher than in the present-day climate. Better resolution of ocean mesoscale eddies enables simulation of more realistic MHWs than low-resolution models. These increases in MHWs under global warming pose a serious threat to LMEs, even if resident organisms could adapt fully to the long-term mean warming.

54 ENVIRONMENTAL SCIENCES↗

Clades of huge phages from across Earth’s ecosystems

Bacteriophages typically have small genomes and depend on their bacterial hosts for replication. Here we sequenced DNA from diverse ecosystems and found hundreds of phage genomes with lengths of more than 200 kilobases (kb), including a genome of 735 kb, which is—to our knowledge—the largest phage genome to be described to date. Thirty-five genomes were manually curated to completion (circular and no gaps). Expanded genetic repertoires include diverse and previously undescribed CRISPR–Cas systems, transfer RNAs (tRNAs), tRNA synthetases, tRNA-modification enzymes, translation-initiation and elongation factors, and ribosomal proteins. The CRISPR–Cas systems of phages have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phages may repurpose bacterial CRISPR–Cas systems to eliminate competing phages. We phylogenetically define the major clades of huge phages from human and other animal microbiomes, as well as from oceans, lakes, sediments, soils and the built environment. We conclude that the large gene inventories of huge phages reflect a conserved biological strategy, and that the phages are distributed across a broad bacterial host range and across Earth’s ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

A 2-million-year-old ecosystem in Greenland uncovered by environmental DNA

Late Pliocene and Early Pleistocene epochs 3.6 to 0.8 million years ago had climates resembling those forecasted under future warming. Palaeoclimatic records show strong polar amplification with mean annual temperatures of 11–19 °C above contemporary values. The biological communities inhabiting the Arctic during this time remain poorly known because fossils are rare. Here we report an ancient environmental DNA (eDNA) record describing the rich plant and animal assemblages of the Kap København Formation in North Greenland, dated to around two million years ago. The record shows an open boreal forest ecosystem with mixed vegetation of poplar, birch and thuja trees, as well as a variety of Arctic and boreal shrubs and herbs, many of which had not previously been detected at the site from macrofossil and pollen records. The DNA record confirms the presence of hare and mitochondrial DNA from animals including mastodons, reindeer, rodents and geese, all ancestral to their present-day and late Pleistocene relatives. The presence of marine species including horseshoe crab and green algae support a warmer climate than today. The reconstructed ecosystem has no modern analogue. The survival of such ancient eDNA probably relates to its binding to mineral surfaces. Our findings open new areas of genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities from two million years ago using ancient eDNA.

58 GEOSCIENCES↗

A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States

Mapped monthly data products of surface ocean acidification indicators from 1998 to 2022 on a 0.25° by 0.25° spatial grid have been developed for eleven U.S. large marine ecosystems (LMEs). The data products were constructed using observations from the Surface Ocean CO 2 Atlas, co-located surface ocean properties, and two types of machine learning algorithms: Gaussian mixture models to organize LMEs into clusters of similar environmental variability and random forest regressions (RFRs) that were trained and applied within each cluster to spatiotemporally interpolate the observational data. The data products, called RFR-LMEs, have been averaged into regional timeseries to summarize the status of ocean acidification in U.S. coastal waters, showing a domain-wide carbon dioxide partial pressure increase of 1.4 ± 0.4 μatm yr -1 and pH decrease of 0.0014 ± 0.0004 yr -1 . RFR-LMEs have been evaluated via comparisons to discrete shipboard data, fixed timeseries, and other mapped surface ocean carbon chemistry data products. Regionally averaged timeseries of RFR-LME indicators are provided online through the NOAA National Marine Ecosystem Status web portal.

54 ENVIRONMENTAL SCIENCES↗

Stochasticity, succession, and environmental perturbations in a fluidic ecosystem

Unraveling the drivers of community structure and succession in response to environmental change is a central goal in ecology. Although the mechanisms shaping community structure have been intensively examined, those controlling ecological succession remain elusive. To understand the relative importance of stochastic and deterministic processes in mediating microbial community succession, a unique framework composed of four different cases was developed for fluidic and nonfluidic ecosystems. The framework was then tested for one fluidic ecosystem: a groundwater system perturbed by adding emulsified vegetable oil (EVO) for uranium immobilization. Our results revealed that groundwater microbial community diverged substantially away from the initial community after EVO amendment and eventually converged to a new community state, which was closely clustered with its initial state. However, their composition and structure were significantly different from each other. Null model analysis indicated that both deterministic and stochastic processes played important roles in controlling the assembly and succession of the groundwater microbial community, but their relative importance was time dependent. Additionally, consistent with the proposed conceptual framework but contradictory to conventional wisdom, the community succession responding to EVO amendment was primarily controlled by stochastic rather than deterministic processes. During the middle phase of the succession, the roles of stochastic processes in controlling community composition increased substantially, ranging from 81.3% to 92.0%. Finally, there are limited successional studies available to support different cases in the conceptual framework, but further well-replicated explicit time-series experiments are needed to understand the relative importance of deterministic and stochastic processes in controlling community succession.

54 ENVIRONMENTAL SCIENCES↗